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研究生: 林士捷
Lin, Shih-Chien
論文名稱: 台灣造山褶皺逆衝帶孕震構造分析—以六甲地區為例
Seismogenic Structures of Orogenic Fold-and-Thrust Belt in the Liuchia Area, Taiwan
指導教授: 李恩瑞
Lee, En-Jui
學位類別: 碩士
Master
系所名稱: 理學院 - 地球科學系
Department of Earth Sciences
論文出版年: 2023
畢業學年度: 111
語文別: 中文
論文頁數: 64
中文關鍵詞: 褶皺逆衝帶造山帶孕震構造
外文關鍵詞: fault-and-thrust belt, orogenic belt, seismogenic structure, earthquakes relocation
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  • 台灣從新生代開始因歐亞板塊與菲律賓海板塊碰撞形成造山運動持續至今,其中褶皺逆衝帶的斷層為主要大規模地震的孕震帶例如:1999 集集地震的車籠埔斷層。台灣西南部的六甲斷層一為褶皺逆衝帶的斷層之一,根據中央氣象局地震潛勢預測,六甲斷層帶是未來 10 年內台灣西南部最有可能發生規模 6.0 以上地震的地方,並且六甲斷層帶在沉寂 20 年左右,於 2020 年 8 月及 10 月分別發生兩起地震群事件,不免讓人擔心是否進入活躍期。
    本次研究區域位於台南市東北方,地質屬於西部麓山帶,區域內有多條中央地質調查所所劃定之活動斷層存在,其中六甲斷層鄰近台灣南部的科學重鎮—台南科學園區,若發生大規模地震,勢必造成嚴重的人員傷亡與龐大的經濟損失。本研究希望從地震數量、分布等,進一步了解六甲斷層帶的地下細部構造,有益於了解褶皺逆衝帶構造和台灣造山運動。
    本次研究使用中央氣象局地震觀測網(CWBSN)、台灣強地動觀測網(TSMIP)與台灣寬頻地震觀測網(BATS)於 2020 年 8 月至 11 月的連續地震觀測資料,並使用機器學習模型(Attention Recurrent-Residual U-Net,ARRU)自動挑選潛在 P 波、S 波到時,並以此進行反投影找出潛在的地震事件,再根據其結果對地震進行重新定位與截切地震波形製作地震目錄,接著使用 Weighted Template-Matching Algorithm(WTMA)其原理依靠波形相似度尋找小規模地震,最後使用 GrowClust3D 分群重新定位完成地震目錄。
    經過重新定位結果,在 2020 年 8 月到 11 月間六甲斷層下方 8~15 公里為主要孕震構造,8 月 19 日地震群在六甲斷層南段,為低角度向東傾斷層所造成,10 月 17日地震群在六甲斷層北段,為低角度向西傾斷層所造成,南、北段發震構造有顯著差異,從深度及構造來看,兩起地震群並非地表六甲斷層所引起,並且我們推論南段為褶皺逆衝帶的滑脫斷層所造成,北段則因為對於地底深部認知不足,因此我們提出了兩種可能成因:預存正斷層反轉再激活或深部逆衝斷層之背衝斷層所形成。

    Taiwan is located at the boundary between the Eurasian Plate and the Philippine Sea Plate, and it has been undergoing active tectonic movements since the middle to late Miocene. However, before the mountain-building phase, the western part of Taiwan was situated at a passive continental margin and experienced at least two periods of rifting events, resulting in complex geological structures in the region. On August 19 and October 17, 2020, seismic events with magnitudes of M L 4.7 and M L 5.2 occurred in the Liuchia area,Taiwan. To investigate the seismic structures in this region, We employed machine learning models, Attention Recurrent-Residual U-Net (ARRU), along with the backprojection method to establish earthquake locations. Then use Weighted Template-Matching Algorithm (WTMA) to detect small-scale earthquakes. Subsequently, the GrowClust3D method was employed for relative earthquake relocation. The results revealed that the seismic cluster on August 19 was located in the southern segment of the Liuchia fault, while the cluster on October 17 was in the northern segment of the fault. Moreover, significant differences were observed in the seismic structures between the southern and northern segments. Based on depth and structural analysis, both seismic clusters were found not to be directly related to the surface expression of the Liuchia fault. Instead, the seismic structures in the southern segment were caused by a roughly 30° east-dipping fault, whereas those in the northern segment were induced by a approximately 45° west-dipping fault. We infer that the southern segment may be caused by a detachment fault, while the northern segment could be the result of either reactivated pre-existing normal faulting or a backthrust fault associated with deep-seated thrusting.

    中文摘要 i 英文摘要 iii 致謝 vii 目錄 viii 圖目錄 x 表目錄 xii 第一章 緒論 1 1.1 研究動機 1 1.2 區域概況 4 1.2.1 地形與地層 8 1.2.2 地質構造 8 1.3 論文架構 10 第二章 前人文獻 12 2.1 六甲斷層 12 2.2 褶皺逆衝帶 14 2.3 台南盆地 18 第三章 研究方法 23 3.1 資料來源 23 3.2 速度模型 25 3.3 研究流程 25 3.4 機器學習自動挑波相與反投影定位(ARRU_BP) 26 3.4.1 ARRU機器學習模型 27 3.4.2 ARRU_BP流程 27 3.5 WTMA 31 3.6 GrowClust3D 32 3.7 ISOLA 37 第四章 研究成果 38 4.1 ARRU_BP定位結果 38 4.2 WTMA解算結果 41 4.3 ISOLA解算成果 42 4.4 GrowClust3D重新定位結果 44 4.4.1 地震深度分布 48 4.4.2 地震分布剖面圖 50 第五章 討論 54 5.1 8月19日地震群事件 54 5.2 10月17日地震群事件 55 5.3 8月與10月地震群比較 57 第六章 結論 59 參考文獻 60

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